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Run Semgrep static analysis scan on a codebase using parallel subagents. Supports two scan modes — "run all" (full ruleset coverage) and "important only" (high-confidence security vulnerabilities). Automatically detects and uses Semgrep Pro for cross-file taint analysis when available.
Passed 15 of 22 test cases with the skill, and 5 of 22 without it.
and 9 more in the full report
10 fixed5 passed either way7 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
After individual language scans produce SARIF reports in `$OUTPUT_DIR/raw`, what exact script and paths combine them into the final consolidated result?
| Checked | Without skill | With skill |
|---|---|---|
| Executes `uv run scripts/merge_sarif.py` passing `$OUTPUT_DIR/raw` and `$OUTPUT_DIR/results/results.sarif` as arguments. | Missed | Passed |
The instructions your model reads when the skill loads.
Run a Semgrep scan with automatic language detection, parallel execution via subagents when the host supports delegation (otherwise scan sequentially), and merged SARIF output.
--metrics=off — Semgrep sends telemetry by default; --config auto also phones home. Every semgrep command must include --metrics=off to prevent data leakage during security audits.semgrep-rule-creator skillsemgrep-rule-variant-creator skillAll scan results, SARIF files, and temporary data are stored in a single output directory.
OUTPUT_DIR../static_analysis_semgrep_1. If that already exists, increment to _2, _3, etc.In both cases, always create the directory with mkdir -p before writing any files.
# Resolve output directory
if [ -n "$USER_SPECIFIED_DIR" ]; then
OUTPUT_DIR="$USER_SPECIFIED_DIR"
test cases passed, vs 5 / 22 without
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